Launching a Spark application with the Amazon Redshift integration for Apache Spark - Amazon EMR

Launching a Spark application with the Amazon Redshift integration for Apache Spark

To use the integration with EMR Serverless 6.9.0, you must pass the required Spark-Redshift dependencies with your Spark job. Use --jars to include Redshift connector related libraries. To see other file locations supported by the --jars option, see the Advanced Dependency Management section of the Apache Spark documentation.

  • spark-redshift.jar

  • spark-avro.jar

  • RedshiftJDBC.jar

  • minimal-json.jar

Amazon EMR releases 6.10.0 and higher don't require the minimal-json.jar dependency, and automatically install the other dependencies to each cluster by default. The following examples show how to launch a Spark application with the Amazon Redshift integration for Apache Spark.

Amazon EMR 6.10.0 +

Launch a Spark job on Amazon EMR Serverless with the Amazon Redshift integration for Apache Spark on EMR Serverless release 6.10.0 and higher.

spark-submit my_script.py
Amazon EMR 6.9.0

To launch a Spark job on Amazon EMR Serverless with the Amazon Redshift integration for Apache Spark on EMR Serverless release 6.9.0, use the --jars option as shown in the following example. Note that the paths listed with the --jars option are the default paths for the JAR files.

--jars 
    /usr/share/aws/redshift/jdbc/RedshiftJDBC.jar,
    /usr/share/aws/redshift/spark-redshift/lib/spark-redshift.jar,
    /usr/share/aws/redshift/spark-redshift/lib/spark-avro.jar,
    /usr/share/aws/redshift/spark-redshift/lib/minimal-json.jar
spark-submit \
  --jars /usr/share/aws/redshift/jdbc/RedshiftJDBC.jar,/usr/share/aws/redshift/spark-redshift/lib/spark-redshift.jar,/usr/share/aws/redshift/spark-redshift/lib/spark-avro.jar,/usr/share/aws/redshift/spark-redshift/lib/minimal-json.jar \
  my_script.py